Ada Diamonds

Search loose lab diamonds

search_diamonds

Read-only

Search Ada Diamonds' live loose lab grown diamond inventory by shape, carat weight, price, color, clarity, and cut. Returns currently available stones with their grading report numbers and product URLs. Use this for any question about what diamond a budget can buy. MCP Apps-enabled: hosts that support MCP Apps render the results as an interactive card grid.

Input Schema

TableJSON Schema

Name	Required	Description
`cut`	No	Cut grade: Ideal, Excellent, or Very Good
`sort`	No	Result order: price_asc (default relevance), price_desc, carat_asc, or carat_desc
`color`	No	Color grade, D (colorless) through K
`limit`	No	Maximum number of results to return, 1 to 50 (default 10)
`shape`	No	Cut shape: Round, Oval, Cushion, Emerald, Pear, Radiant, Asscher, Princess, or Marquise
`clarity`	No	Clarity grade: FL, IF, VVS1, VVS2, VS1, VS2, SI1, or SI2
`context`	Yes	Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
`llm_model`	Yes	The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
`max_carat`	No	Maximum carat weight, e.g. 2
`max_price`	No	Maximum price of the loose stone in US dollars
`min_carat`	No	Minimum carat weight, e.g. 1 or 1.5
`min_price`	No	Minimum price of the loose stone in US dollars
`conversation_id`	No	Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.

Output Schema

TableJSON Schema

Name	Required	Description
`kind`	Yes	Which catalog the results come from
`items`	Yes	The matching entries, best match first
`query`	Yes	The filters that were applied (only the ones you sent)
`shown`	Yes	How many entries are in `items`
`total`	Yes	How many catalog entries matched before the limit
`browseUrl`	Yes	Web page listing the full catalog for this search

Schema Changelog

Changes observed during successful MCP inspections.

Changed5 schema fields changedSep 18, 2026

removedInput schema / additionalProperties
```
Removed value: -false
```

addedInput schema / properties / context

Added value: +{
+  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
+  "type": "string"
+}

addedInput schema / properties / conversation_id

Added value: +{
+  "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
+  "type": "string"
+}

addedInput schema / properties / llm_model

Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}

addedInput schema / required

Added value: +[
+  "context",
+  "llm_model"
+]

Changed1 schema field changedSep 2, 2026
- addedInput schema / additionalProperties
```
Added value: +false
```
First observedSep 1, 2026

TDQS

A4.1/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds value by disclosing that results are 'currently available stones' (live inventory), that it returns grading report numbers and product URLs, and that MCP Apps hosts render results as an interactive card grid. This goes beyond the annotations without contradicting them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences and front-loads the core purpose and scope. The first sentence is dense but efficient. The second sentence gives a clear usage cue. The third sentence about MCP Apps is useful but slightly tangential to the core invocation logic; it earns its place as behavioral context but could be trimmed. Overall, no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a search tool with 13 parameters, 100% schema coverage, an output schema, and read-only annotations, the description covers the essential invocation context: what is searched, what filters apply, what results contain, and when to use it. The only minor gap is that it doesn't explain the default sort behavior beyond what the schema already states, but the schema covers that. The description is complete enough for an agent to select and call the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 13 parameters. The description adds a little context by naming the filter dimensions (shape, carat, price, color, clarity, cut) and noting the sort default ('price_asc (default relevance)'), but it doesn't add meaning beyond what the schema provides. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Search'), a specific resource ('Ada Diamonds' live loose lab grown diamond inventory'), and enumerates the filter dimensions (shape, carat, price, color, clarity, cut). It also distinguishes itself from siblings by focusing on loose lab-grown diamonds and budget-based queries, which separates it from search_engagement_rings and search_jewelry.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use this for any question about what diamond a budget can buy,' which gives clear context for when to invoke it. It doesn't explicitly name alternatives or exclusions, but the sibling list and the phrase 'loose lab grown diamond inventory' imply when other tools (e.g., search_engagement_rings, search_jewelry) would be more appropriate. A clear when-to-use is present, but no explicit when-not-to-use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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